Method and system for tuning of movement disorder therapy devices

ABSTRACT

A system and method for tuning the parameters of a therapeutic medical device comprises a movement measurement data acquisition system capable of wireless transmission; processing comprising kinematic feature extraction, a scoring algorithm trained using scores from expert clinicians, a therapeutic device parameter setting adjustment suggestion algorithm preferably trained using the parameter setting adjustment judgments of expert clinicians; and a display and/or means of updating the parameter settings of the treatment device. The invention facilitates the treatment of movement disorders including Parkinson&#39;s disease, essential tremor and the like by optimizing deep brain stimulation (DBS) parameter settings, eliminating as much as possible motor symptoms and reducing time and costs of surgical and outpatient procedures and improving patient outcomes. In preferred embodiments, the system provides recommendations for treatment which may be semi-automatically or automatically applied to update the parameter settings of a treatment device such as a DBS implant.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.13/153,063, which was filed on Jun. 3, 2011, which was acontinuation-in-part of both U.S. patent application Ser. No.12/818,819, now abandoned, which was filed on Jun. 18, 2010, and U.S.patent application Ser. No. 12/250,792, which was filed on Oct. 14,2008.

STATEMENT REGARDING FEDERALLY-SPONSORED RESEARCH OR DEVELOPMENT

The U.S. Government has a paid-up license in this invention and theright in limited circumstances to require the patent owner to licenseothers on reasonable terms provided for by the terms of grant number1R44AG033520 awarded by the National Institutes of Health, NationalInstitute on Aging.

BACKGROUND OF THE INVENTION (1) Field of the Invention

The present invention relates to therapeutic medical apparatus, systems,devices and/or methods, and more particularly, to apparatus and methodsfor using neural stimulation to alleviate the symptoms of movementdisorders, such as those associated with Parkinson's disease, essentialtremor, dystonia, and Tourette's syndrome, including tremor,bradykinesia, rigidity, gait/balance disturbances, and dyskinesia.

(2) Technology Review

A current trend in the treatment of diseases identified as beingassociated with the central nervous system is the stimulation of targetareas of the central nervous system to effect therapeutic benefit. Suchstimulation has been accomplished with, for example, implantedelectrodes that deliver electrical stimulation to target brain regions;one class of electrical neural stimulation devices has been categorizedunder the name “deep brain stimulation” (DBS). Although the exactneurological mechanisms by which DBS therapies succeed are complex andare not yet fully understood, such therapies have proven effective intreating Parkinson's disease motor symptoms (such as tremor,bradykinesia, rigidity, and gait disturbances), and investigation intothe use of DBS for the treatment of this and other neurological andmental health disorders, including major depression,obsessive-compulsive disorder, tinnitus, obesity, criminal tendencies,and antisocial disorders, is ongoing.

Typically, medication for Parkinson's disease (PD) consists of Levodopato alleviate symptoms. Over time, however, the medication has reducedefficacy and shows increased occurrence of side effects such asdyskinesias. Once side effects outweigh benefits, patients consider deepbrain stimulation (DBS). An electrode/wire lead is implanted in aspecific location in the brain which shows hyperactivity in PD patientsand is sensitive to electrical stimulation. PD target sites are thesubthalamic nucleus (STN) or globus pallidus internus (GPi). TheEssential tremor and Parkinson tremor target site is generally theventral intermedius nucleus of the thalamus (VIM). Electrical pulsescharacterized by amplitude (volts), current (amps), frequency (Hz), andpulse width (microseconds) are regulated by an implantable pulsegenerator (IPG) placed beneath the skin on the chest. Stimulationaffects motor symptoms on the contralateral side, i.e., right sidetremor will be treated on the left brain. After a patient has beenimplanted and recovered, programming sessions will fine tune stimulationsettings described above in order to minimize symptom severity, minimizeside effects, and maximize IPG battery life span. Although medication isnot eliminated, it is typically reduced significantly. DBS efficacydecreases over time as the body adjusts to stimulation and proteinbuildup around electrode lead attenuates electrical field. Programmingsessions are required throughout the patient's lifetime, though thefrequency of adjustments are typically greater at first.

A typical implanted DBS stimulation lead consists of a thin insulatedneedle comprising four platinum/iridium electrodes spaced 0.5 or 1.5 mmapart along the length of the lead. One or multiple leads may beimplanted in a target brain region or regions to providesymptom-inhibiting high-frequency stimulation, although some researchsuggests that excellent results can be achieved even when the lead isimplanted distant from a target region. A DBS lead is connected to animplantable pulse generator (IPG), which serves as a controller andpower source, via an extension cable tunneled subcutaneously to asubcutaneous pocket in the chest or abdominal cavity. The IPG typicallyincludes a battery and circuitry for telemetered communication with anexternal programming device used to adjust, or “tune,” DBS leadstimulation parameters, which may include stimulation frequency,amplitude, pulse width (or wavelength), and contact configuration (thatis, the selection of which electrodes are utilized from among the fourelectrodes available on a lead, and, if two or more electrodes areactive, the relative polarity of each). These parameters are initiallyset during implantation surgery and are then further fined-tuned in theoutpatient clinic or in a doctor's office following surgery to maximizetherapeutic benefit and minimize undesirable stimulation-induced sideeffects. The first such tuning session usually takes place several weeksfollowing implantation surgery, after the patient has recovered andinflammation at the lead placement site has subsided.

While the above-described equipment and procedures are typical as of thefiling of this application, variations and refinements may becomecommonplace as neural implant technology advances. Conceivably, uses ofa multiplicity of DBS leads or networks of DBS leads may provide greatercoverage, enabling the stimulation of larger and more varied targetareas, and miniaturization and improved telemetry may obviate the needfor the extension cable and/or the IPG altogether as leads becomeself-powering and/or self-controlling or permit for built-in telemetry.Advances in nanotechnology and materials may also allow DBS leads in thefuture to become self-repositioning, self-cleaning, or resistant tobiological rejection for improved long-term therapeutic operation andmore precisely targeted implantation.

The current standard in evaluating the severity of movement disordersymptoms in Parkinson's disease is the Unified Parkinson's DiseaseRating Scale (UPDRS) used to score motor tests, many of which involverepetitive movement tasks such as touching the nose and drawing the handaway repeatedly, or rapidly tapping the fingers together. A battery ofexercises, typically a subset of the upper extremity motor section ofthe UPDRS, is normally completed during DBS lead placement surgery andsubsequent programming sessions to evaluate performance while aclinician qualitatively assesses symptoms. Each test is evaluated by aclinician based solely on visual observation and graded on a scale thatranges from 0 (insevere) to 4 (severe).

During DBS implantation surgery, various lead placement strategies areused, including inversion recovery imaging, reformatted anatomicalatlases, and formula coordinates based on known landmarks. Implantationlocation is verified and adjusted based on electrophysiological mappingusing techniques such as microelectrode recording and micro and macrostimulation. Currently, lead placement and stimulation parameters aremodified based on subjective motor examinations such as clinicalobservation such as the UPDRS motor tasks during the implantationprocedure. After lead placement, patient motor symptoms are evaluated inresponse to a set of stimulation parameters. Stimulation parameters arethen adjusted, and motor exam repeated. This trial-and-error process ofadjusting parameters and monitoring patient response is continued untilan optimal electrode position and stimulation set are established.During this programming or “tuning” process, the clinician subjectivelyassesses motor symptom improvement.

Postoperatively, assessing DBS response and reprogramming stimulationparameters require a significant time commitment. Several stimulationparameters can be modified, including electrode polarity, amplitude,current, pulse width, and frequency. DBS programming and patientassessment may be performed by a variety of healthcare professionals,including movement disorder neurologists, neurosurgeons, fellows,occupational and physical therapists, and nurses. Stimulationoptimization must be performed based on results of an exam such as theUPDRS, with the patient in four states (off medication/off DBS, offmedication/on DBS, on medication/off DBS, and on medication/on DBS) perthe Core Assessment Program for Surgical Intervention Therapies inParkinson's disease (CAPSIT-PD) protocol. The process of DBS adjustmentis iterative and largely involves trial-and-error. Retrospective studieshave found that DBS programming sessions take more than twice as long astypical evaluations by movement disorder neurologists. Programmingsessions are typically limited to 1-3 hours since longer sessions resultin patient fatigue or lightheadedness. Programming and patientassessment from preoperatively to one year after surgery requiresapproximately 30 hours of nursing time per patient.

Clinicians presently lack tools that combine physiological, electrical,and behavioral data to optimize electrode placement and stimulatorprogramming. Optimizing electrode placement and stimulation parametersimproves patient outcome by alleviating motor symptoms and minimizingcomplications. The present invention addresses this need for improvedelectrode placement and adjustment of deep brain stimulation parametersby providing a repeatable, automated or semi-automated tool that canassist stimulation parameter tuning during surgical electrode placementand outpatient programming sessions. In particular, the presentinvention aims to provide methods for the collection and transmission ofobjective biokinetic data during these procedures, which data is thenprocessed to output objective movement disorder symptom severitymeasures on a continuous scale in real-time to guide clinician decisionmaking. The improved resolution and repeatable results of the presentinvention should reduce time and costs of DBS procedures as well asimprove patient outcomes.

It is therefore the object of the present invention to coupleautomatically-assigned quantitative motor assessments with proceduresand practices for DBS implantation and parameter tuning insemi-automatic and automatic ways to provide improved and less costlymovement disorder patient therapy.

Existing systems for quantifying Parkinson's disease motor symptoms aredescribed in this application's parent application, U.S. patentapplication Ser. No. 12/250,792, which is herein incorporated byreference, and which describes a novel system for measuring motordysfunction symptoms and computing measures based on UPDRS scorestherefrom. Preferably, the system and methods described therein areincorporated, in whole or in part, into the present invention as a meansof automatic symptom quantification. The resultant scores objectivelyquantify movement disorder symptoms advantageously using a scale that isfamiliar to clinicians.

SUMMARY OF THE INVENTION

The present invention relates to methods for automatically andsemi-automatically adjusting treatment parameters in therapy systems.The present invention further provides methods of quantifying movementdisorders for the treatment of patients who exhibit movement disordersymptoms such as may be caused by Parkinson's disease. The presentinvention further relates to a symptom quantification algorithm trainedusing reference data, particularly where the data comprisesclinician-assigned movement disorder test scores given on the UnifiedParkinson's Disease Rating Scale, and more particularly when the scoresare given for tests from the UPDRS motor examination. The presentinvention further relates to a therapeutic device parameter adjustmentalgorithm, particularly where the algorithm is trained using referencedata, and more particularly where the data comprises clinician-assignedtherapeutic device parameter adjustments and which data thereforerepresents the judgment of one or more expert clinicians.

Objective quantification of a subject's movement disorder symptoms,including tremor, bradykinesia, dyskinesia, and gait/balancedisturbances requires, as a first step, a measurement of the movement.This measurement can be performed by measuring a single parameter ordifferent parameters; the parameter or parameters being measured mayinclude linear or rotational displacement, velocity, or acceleration,electromyographic (EMG) signals, or any other parameter that could givea quantitative indication of motion; and the part of the body beingmeasured for motion may be a limb (as at a wrist, ankle, or finger) ormay be the trunk of the body (as at a shoulder or torso) and by othertechniques known to those skilled in the art. Sensors used for measuringbody motion include gyroscopes and accelerometers, preferablyminiaturized; electromagnets; EMG; video; or other sensors known tothose skilled in the art. Other systems that can be used to detect andmeasure body motion include motion capture systems, machine visionsystems, sonic or laser Doppler velocity transducers, infrared systems,GPS, or any other system known to those skilled in the art. The movementdata acquisition system, or “movement measuring apparatus,” used in thepresent invention may incorporate one or more of any of the abovesensors or systems. A pre-existing movement data acquisition system,such as the one described in patent application Ser. No. 11/082,668,herein incorporated by reference, may similarly be used. In the presentdisclosure, “movement data” is construed as including, but not beinglimited to, any signal or set of signals, analog or digital,corresponding to movement of any part of the body or multiple parts ofthe body, independently or in conjunction with each other. Movement maybe continuously measured over long time spans, or may be measured onlyover a short time span, for example, during the period of only one orseveral tests taken from or modified from the UPDRS motor exam. Incertain embodiments of the present invention, the measurement timeneeded to produce a score substantially predictive of a UPDRS score fora given test on the UPDRS motor exam is acquired during a test lastingno more than about 20 seconds. Further, in certain embodiments of thepresent invention, the measurement time needed to produce scoressubstantially predictive of a set of multiple UPDRS scores for multiplegiven tests on the UPDRS motor exam is acquired during a test preferablylasting no more than about 30 minutes. More preferably, the measurementtime does not exceed 15 minutes. More preferably, the measurement timedoes not exceed 10 minutes. Even more preferably, the measurement timedoes not exceed 5 minutes. Even still more preferably, the measurementtime does not exceed 3 minutes. Still more preferably, the measurementtime does not exceed 1 minute. Still more preferably, the measurementtime does not exceed 30 seconds. Most preferably, the measurement timedoes not exceed 15 seconds.

Following measurement of symptomatic movement, the next step inobjective quantification of a subject's movement disorder symptoms isthe extraction of statistical kinematic features from the acquiredmovement data via processing. This processing may take place during orfollowing data acquisition and may occur within a movement dataacquisition device or within a different processing device, such as apersonal computer, PDA, smart phone, tablet PC, touch screen interface,or the like, with which the acquisition device interfaces, eitherthrough a cable connection or by wireless transmission. Useful kinematicfeatures that may be extracted from gyroscopic data may include, forexample, peak power angular velocity, peak power angle, RMS angularvelocity, frequency, maximum amplitude, maximum peak-to-peak amplitude,mean angular velocity, and wavelet parameters, as well as the covarianceor standard deviation over time of any of these parameters. Usefulkinematic features that may be extracted from accelerometer data mayinclude, for example, peak power acceleration, peak power velocity, peakpower position, RMS acceleration, RMS velocity, RMS position, frequency,maximum amplitude, maximum peak-to-peak amplitude, mean acceleration,and wavelet parameters, as well as the covariance or standard deviationover time of any of these parameters. In a movement data acquisitionsystem, or movement measuring apparatus, that combines a three-axisaccelerometer and a three-axis gyroscope to produce 6 channels ofmovement data, one or any combination of the above kinematic featurescan be extracted from any of the 6 kinematic channels to be used asinputs to a trained algorithm in the next step. The listed kinematicfeatures for the sensors above are intended to be exemplary, and notlimiting; other types of sensors will produce different data from whichdifferent sets of features may be extracted.

The trained algorithm used to process the kinematic features extractedfrom the movement data may comprise, for example, one or more of asimple or multiple linear regression, an artificial neural network, aBayesian network, or a genetic algorithm. The output of the trainedalgorithm may be a single score or multiple scores of any scale; asingle score on the same scale as that of the UPDRS may be preferred incertain applications where simplicity or familiarity is the paramountconcern, while more sophisticated scores and scales may be preferred forother advanced applications, such as those that involve recommendationsfor treatment or closed-loop automated treatment delivery.

Following the step of symptom quantification, a separate algorithmcomputes suggested changes to the therapy system parameter settingsbased on the result of the symptom quantification algorithm and known orpredicted current therapy system parameter settings physiologicalmodels.

Depending on the embodiment of the invention, the current therapy systemparameter settings changes may be input into the algorithm by a humanuser such as a clinician using a hardware or software user interface, ormay be automatically sensed from the DBS parameter settings bycommunicating with a DBS implant or its programmer device, or may beknown because the DBS parameter settings have been reset to some knownbaseline settings or restored to a previously saved settings preset. Theexisting parameter settings might also be predicted or derived based,for example, on observed or measured therapy effectiveness.

Suggested therapy system parameter settings changes are then input intothe therapy system, and their effectiveness is measured using theabove-described method of symptom quantification.

The process of therapy system parameter settings adjustment may remainiterative, but the invention greatly reduces the time and expertiserequired to arrive at optimized stimulation parameter settings,advantageously allowing clinicians with lesser training or experience toadjust parameter settings during patient visits, and to do so in lesstime than is currently required. Additionally, the present inventionincreases access to geographically disparate populations by putting theexpertise into the system and reducing or eliminating the need for anexpert or trained clinician to be present with each subject.

A number of embodiments of the present invention are envisioned in thisdisclosure. These embodiments are examples of the many embodimentsencompassed by the present invention, but do not in any way limit themany other embodiments covered by this disclosure.

In one embodiment, the method for adjusting brain stimulation electrodesin a subject for treating a subject's movement disorder comprises thesteps of applying at least one sensor having a signal to a post-surgicalsubject having an implanted brain stimulation device for treatment of amovement disorder; quantifying at least one symptom of the subject'smovement disorder with the signal from the at least one sensor using aprocessor; outputting the quantification of the at least one symptom toa display; and adjusting the implanted brain stimulation device fortreatment of the movement disorder based at least in part on theoutputted quantification of the at least one symptom. In an embodimentdesigned to assist in optimizing therapy for movement disorders in theextremities, preferably at least two sensors are applied to a finger ofthe post-surgical subject, and the sensors include both an accelerometerand a gyroscope. More preferably, the sensors are packaged in anenclosure weighing altogether no more than about 12 grams and no largerthan about 12 cubic centimeters. Preferably, the movement disordersymptom quantification is based on historical data, which is preferablyUPDRS scores assigned to movement disorder patients by one or moreexpert clinicians. Preferably, the therapy parameter adjustment is basedat least in part on historical data, which preferably comprises recordedadjustments made to brain stimulation devices implanted in movementdisorder patients, the adjustments having been made by at least oneexpert clinician, and preferably multiple expert clinicians.

In another embodiment, the method for adjusting treatment parameters ofa therapeutic medical device in a subject comprises the steps ofapplying at least one sensor having a signal to a subject presentlyusing a therapeutic medical device for treatment of a disorder, thetherapeutic medical device having more than two adjustable parameters;measuring at least one symptom of the subject's disorder with the signalfrom the at least one sensor; selecting at least one parameter of thetherapeutic medical device to adjust; estimating or calculating a levelof adjustment to be applied to the selected at least one parameter ofthe therapeutic medical device using a processor, the estimation orcalculation being based at least in part on the measurement of the atleast one symptom and at least in part on recorded data representing thejudgment of one or more expert clinicians; presenting the estimated orcalculated level of adjustment for the selected at least one parameterof the therapeutic medical device to a medical professional and/or thesubject; and adjusting the at least one parameter of the therapeuticmedical device based at least in part on the estimated or calculatedlevel of adjustment to be made. Preferably, the level of adjustment forthe selected at least one parameter of the therapeutic medical device isestimated or calculated using an artificial neural network trained usingrecorded data representing the judgment of one or more expertclinicians; preferably, this recorded data comprises parameter settingsadjustments made to like therapy devices for multiple patients. Thetherapeutic device may be any of a number of devices, includingstimulation implants such as DBS implants or drug delivery systems suchas those that comprise a drug delivery pump and a drug reservoir.Preferably, the step of adjusting the at least one parameter of thetherapeutic medical device is executed upon the manual or vocalconfirmation of the presented estimated or calculated level ofadjustment, the confirmation being made by a medical professional or thesubject. In other embodiments, the step of adjusting the at least oneparameter of the therapeutic medical device is carried out by a closedloop control system, which automatically adjusts the settings based atleast in part on the estimated or calculated level of adjustment.

Yet another embodiment of the present invention is a system foradjusting the parameters of a deep brain stimulation device implanted ina subject for treating a subject's movement disorder by a clinicianafter surgery, the system comprising a sensor unit comprising anaccelerometer and/or gyroscope, the sensor unit being protected by anenclosure and the sensor unit having an analog signal related to themovement of a subject with a movement disorder, the subject having adeep brain stimulation implant having adjustable parameters; anelectronic module for receiving the analog signal acquired by the sensorunit, the electronic module comprising a memory and an analog-to-digitalconverter for converting the analog signal into a digital signal; aprocessing module for receiving the digital signal and for processingthe signal acquired by the sensor unit, for receiving an input relatedto the subject's deep brain stimulation implant's parameter settingsduring measurement of the analog signal with the sensor unit, and toproduce an output comprising computed adjustments for one or more of theadjustable parameters of the deep brain stimulation implant, the outputbeing based at least in part on the signal acquired by the sensor; and adisplay for receiving the output.

Preferably, the movement measuring apparatus is small, lightweight, andnot cumbersome. In some embodiments of the present invention, themovement measuring apparatus preferably consists only of one or twosensor packages placed only on the wrist and a finger of the subject andhas a mass of no more than about 12 grams. More preferably, the movementmeasuring apparatus consists of a sensor package placed only on thefinger of the subject and weighs no more than half an ounce. Even morepreferably, in other embodiments, the movement measuring apparatus ismachine vision-based and uses a video camera or similar sensor to detectthe motion of the subject without any sensor devices placed on the bodyof the subject.

Additional features and advantages of the invention will be set forth inthe detailed description which follows, and in part will be readilyapparent to those skilled in the art from that description or recognizedby practicing the invention as described herein, including the detaileddescription which follows, the claims, as well as the appended drawings.

It is to be understood that both the foregoing general description andthe following detailed description are merely exemplary of theinvention, and are intended to provide an overview or framework forunderstanding the nature and character of the invention as it isclaimed. The accompanying drawings are included to provide a furtherunderstanding of the invention, and are incorporated in and constitute apart of this specification. The drawings illustrate various embodimentsof the invention and together with the description serve to explain theprinciples and operation of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1. Schematic view of a subject undergoing post-surgical DBSadjustment with one embodiment of the invention.

FIG. 2. Schematic view of a subject undergoing post-surgical DBSadjustment with another embodiment of the invention.

FIG. 3. Flow diagram of the parameter adjustment suggestion algorithm insome embodiments of the present invention.

FIG. 4. Flow diagram of the artificial neural network of the parameteradjustment suggestion algorithm in some embodiments of the presentinvention.

FIG. 5. Graphic depiction of display pages displaying test results andscores, as well as a possible parameter input screen.

FIG. 6. Graphic depiction of tuning maps used to display test resultsand symptom severity measured by the system.

DETAILED DESCRIPTION OF THE INVENTION

The present invention relates to the programming of therapeutic medicaldevices having parameters, and methods and systems for automatically andsemi-automatically adjusting those parameters. In embodiments of theinvention which relate to deep brain stimulation (DBS) implant parametersettings adjustment for the treatment of movement disorder symptoms, theinvention includes a method of objectively quantifying the severity of asubject's movement disorder and a method of deriving optimized parametersettings. The symptom quantification may be reduced to a simple score ona scale equivalent to that of the Unified Parkinson's Disease RatingsScale (UPDRS). The present invention provides a repeatable, automatedtool that can assist stimulation tuning during surgical electrodeplacement and outpatient follow-up, thus optimizing patient outcomes andreducing associated time and costs without adding excessive burden tosubjects or clinicians.

The systems and methods of the various embodiments of the presentinvention are used to analyze, score, and treat various disorders, andespecially movement disorders. Movement disorders for purposes of thisapplication include but are not limited to Parkinson's disease andessential tremor. Some of the treatments used for these disordersinvolve pharmaceutical interventions, fetal cell transplants, surgery,or deep brain stimulation. The efficacy of an intervention is oftenjudged by the intervention's ability to alleviate subject symptoms andimprove subject quality of life. The subject on which the system ormethod is used is a human or another form of animal.

The present invention includes a trained algorithm to determine scoringfrom movement data acquired by a movement measuring apparatus. Thetrained algorithm in part comprises a mathematical model or quantitativerepresentation, used to process kinematic features computed from themovement data and may include some of those steps known to those skilledin the art. In some embodiments of the present invention, the scoringmay done on a continuously variable scale of 0-4 with scoressubstantially similar to or predictive of scores that would be given onthe Unified Parkinson's Disease Ratings Scale by an expert clinician.(“Expert clinician” for the purposes of this application is taken tomean a doctor, nurse, researcher, or other medical or scientificprofessional trained for and experienced in the task of interest, e.g.,motor function assessment using the UPDRS, or DBS programming.)

The Applicants herein incorporate the following U.S. Pat. Appln Nos. byreference: Ser. No. 11/082,668 filed Mar. 17, 2005; Ser. No. 11/432,583filed May 11, 2006; Ser. No. 12/250,792 filed Oct. 14, 2008; and Ser.No. 12/818,819 filed Jun. 18, 2010.

FIG. 1 illustrates the therapeutic device programming (or “tuning,” or“parameter settings adjustment”) process with one embodiment of theinvention. A subject 1 has a therapy device (not shown), which in theillustrated case is a therapy device for the treatment of a movementdisorder, such as a DBS implant. Subject 1 wears a sensor unit 2comprising accelerometers and/or gyroscopes (both not shown) as well asa transmission system (not shown). Preferably, the sensor unit 2comprises three orthogonal accelerometers and three orthogonalgyroscopes. Preferably, these are micro-electrical-mechanical (MEMS)accelerometers or gyroscopes, such as Analog Devices ADXL210accelerometers and Analog Devices ADXRS300 gyroscopes. The transmissionsystem may be wired or wireless, and may communicate via any medium andany transmission protocol known to those skilled in the art. In theillustrated embodiment, the sensor unit 2 communicates sensor readingsto a command module 3 over a small flexible transmission cable 4, thoughthis transmission could also be conducted wirelessly. In the illustratedembodiment, the sensor unit 2 is worn on the middle phalange of themiddle finger and the command module 3 is worn on the wrist using awristband, though the placement of the sensor unit 2 and command module3 may vary depending upon the symptoms of the movement disorder;alternate placements could include the ankle, foot, shoulder, orelsewhere on the trunk of the body or on any part of any extremity.While the illustrated embodiment shows the sensor unit 2 and the commandmodule 3 as having separate enclosures, permitting for a lighter-weightsensor unit 2 that is easily worn on the finger, in alternateembodiments the sensor unit 2 and command module 3 may be integratedinto a single enclosure.

The command module 3 supplies power to the sensor unit 2, stores data inmemory, transmits data, and, in some embodiments, may also acquire andamplify two channels of electromyogram (EMG) (not shown). Preferably, itis controlled by firmware in an Analog Devices ADuC7020 processor. TheDAQ section samples finger sensor unit data at 128 Hz for each of thesix channels. Onboard memory provides 12 hours of data storage. Alithium-based battery provides 12 hours of continuous use and isrechargeable by a computer through a lemo to USB connector cable. Thecommand module 3 also integrates a membrane switch label (not shown)with LED indicators for power and charging (not shown). Three membraneswitches inside the label (not shown) provide on/off control and twosubject diary inputs. The command module 3 may perform rudimentarysignal processing, such as filtering and analog-to-digital conversion,on the movement signals received from the sensor unit 2 beforetransmitting the movement signals to a receiver unit 5. Thistransmission may be wired, but is preferably wireless, advantageouslyproviding the subject the greater comfort and convenience of beinguntethered as well as endowing the system with enhanced safety andportability. The wireless link frees subject motion, which allowsunimpeded and accurate assessment of subject symptoms. In operatingroom, a small untethered system has the added benefits of reducingfurther subject discomfort and not impeding clinical traffic. A wirelesssystem which is not directly connected to any source of AC power has theadded benefit of reducing or eliminating risk of electrical shock.Preferably, the wireless transmission is robust and operates in afrequency band designated for hospital use. Preferably, the radio is aBluetooth radio operating in the 2.4 GHz band. More preferably, radiotransmission occurs over the Wireless Medical Telemetry Service (WMTS),dedicated by the FCC to wireless medical equipment used in hospitals,which comprises the frequencies 608 to 614 MHz, 1395 to 1400 MHz and1429 to 1432 MHz. Preferably, radio communication is accomplished usinga mix of traditional heterodyning techniques along with newer softwareradio techniques. For example, receiver structure consists of a bandselect function of either 608-614 MHz or 1395-1432 MHz, followed by aheterodyning operation. The lower frequency band undergoes one frequencytranslation while the upper undergoes two frequency translations. Forthe low band (608-614 MHz) the signal is translated to 44 MHz where itis then sampled by an A/D converter and demodulated in the “sampled”domain. The high band is translated first to the lower frequency band(608-614 MHz) and processed in the same fashion. The software radiodemodulation approach accommodates many different data rates andmodulation formats and advantageously allows future radio upgrades to beimplemented simply by changing the signal processing program opposed tonecessitating an entire analog hardware redesign. The low band transmitsignal is a simple frequency source modulated with appropriateinformation. For the high band transmit signal, the same signal used forthe low band transmit signal is mixed with a high frequency signal toproduce the desired output. For transmitter operation, the signalprocessing hardware generates the modulating signal for all differentsignal formats and data rates. The signal processing hardware outputs amodulating signal input to an oscillator circuit that creates themodulated transmit signal. The modulated signal, for the high band, usesthe low band modulator and translates that signal to the properoperating frequency. Since the modulator is the same for both low andhigh bands it ensures the same signal quality regardless of operationband. Since the radio is a transceiver (two-way link), the design canserve as a master or slave; thus the same design can be employed in thecommand module 3 as well as in the receiver unit 5.

Data may also be collected in an on-board memory contained within thecommand module 3 and downloaded to the tablet computer 6 later,advantageously allowing the subject to wear the sensor unit 2/commandmodule 3 at home for more prolonged symptom monitoring.

The receiver unit 5 may be integrated into some larger system—forexample, it may consist of a Bluetooth receiver integrated into a devicesuch as a laptop or tablet computer, a cellular phone, etc.—or it may aseparate device built into an enclosure. In the illustrated embodiment,the receiver unit 5 is connected to a tablet computer 6 via one of theUSB ports (not shown, in a dongle-style connection that advantageouslyeliminates a cable), is powered thereby, and comprises a radio frequencytransceiver capable of 2-way radio frequency communication with thecommand module 3. Power regulation and USB-based data transmissionprotocols may be among any known in the art. The receiver unit 5 may be,in some embodiments, an off-the-shelf Bluetooth USB adapter dongle.

Tablet computer 6 is used to collect data transmitted from the controlmodule 3, allow user inputs to store and track motor performance andtherapy device parameter settings, and provide clinicians with real-timesymptom quantification feedback. The tablet computer 6 of theillustrated embodiment may be any computing device with a user interface7, including a smart phone, PDA, laptop computer, desktop computer,iPhone, iPad, or the like. Preferably, the tablet computer 6 islightweight and portable, allowing for its easy transport within anoperating room, and includes a touch screen. In some embodiments, thetablet computer 6 may be equipped with a clip or hanger (not shown) foreasy mounting to an operating room pole.

The user interface 7 may be visual, preferably comprising a touchscreen, or it may be an audio interface that accepts and transmitsspoken commands. The user interface 7 preferably provides several keycomponents and an overall software wrapper. First, it preferablyprovides a main menu (not shown) to access all software featuresincluding a subject database (not shown), the tuning assistant softwarewhich runs the therapy device parameter settings tuning algorithm, andsoftware for automatically generating clinical reports following tuningsessions. Next, it preferably provides a module to view real-time motiondata transmitted by the sensor unit 2/command module 3, helping ensureproper setup and communication prior to clinical therapy deviceprogramming. The user interface 7 also preferably communicates with thesystem registry to store system parameters and clinician preferredsettings. Finally, a help menu (not shown) with troubleshooting guidesand frequently asked questions is preferably included.

Subject data management is an important aspect of clinically-usedembodiments of the present invention. Preferably, the format of thesoftware used with the system is designed for a high volume subjectdatabase. Any database known in the art may be used but is preferablyone which scales well to accommodate thousands or tens of thousands ofsubjects. Preferably, the database has fields for subject history,including the subject's surgery dates, a running list of the subject'sclinical sessions (past and/or future scheduled), the subject's primaryphysician, neurologist, medication dosage, etc. Preferably, the subjectis also programmed with the ability to import e-mails and otherdocuments into the subject history, and to export a standardized patientinformation sheet (reporting). Preferably, the database is programmed soas to permit all stored subject information to conform HIPPA guidelinesfor patient privacy and confidentiality.

A programmer unit 8 is used by the clinician to program the subject'stherapy device, that is, to adjust the therapy device's parametersettings.

Alternatively, the sensor unit 2 may transmit to a server or group ofservers such as with cloud computing whereby the data resides on suchserver or group of servers and can be accessed at the point of testingor some remote location for review by a clinician or doctor. In allexchange of information that occurs in the above example and in allother embodiments of the present invention, it is important thatinformation be exchanged securely and in ways that do not improperlydisclose a subject's identity. Because of this, in certain preferredembodiments, all personal information of a subject is stored securely ata remote database and is accessible only through a secure networkconnection wherein both the database and connection protocol arecompliant with standards required by the health insurance portabilityand accountability act (HIPAA). Often, this will require encryption ofthe data to eliminate the possibility that the data can be read by athird party and many preferred embodiments of the present inventioninclude the use of data encryption.

As indicated in the above example, various embodiments of the presentinvention can involve sending a movement disorder monitoring device homeor to another remote location with a subject to be used for movementdisorder testing away from a physician's or clinician's place ofpractice. Once the subject arrives home, the movement disordermonitoring device is placed in the subject's home where it may bepowered by either a single or multiple on-board batteries or by anotherpower source in the subject's home such as a standard 120 voltalternating current outlet. Once in the home a display unit may, atintermittent times selected by the programming physician or clinician,alert the subject of the need to perform certain movement disorderevaluation tasks. At these times, the display unit may produce a sound,provide a visual alert on its display screen, or a combination of bothas a way to alert the subject. In response to the alert the subject willplace at least one sensor on his or her extremity(ies) as instructed bythe display unit and will proceed to follow other instructions providedregarding how to properly complete certain tasks used to evaluate theseverity of the subject's movement disorder symptoms. In certainembodiments, the subject may be video recorded by the camera of thedisplay unit so that a physician can at a later time verify that thetasks were indeed correctly completed. Preferably, the subject will alsoanswer other questions at this time regarding a subject'sself-assessment of his or her symptoms and the subject's adherence toand use of treatments prescribed by the subject's physician or anotherclinician. Such questions may consist of inquiries related to thesubject's perception of the present severity of the subject's symptoms,the subject's most recent dose of pharmaceutically-based treatment, thesubject's activity level throughout the day, and other similar pertinentinformation that is desired to be known by the physician to help betterunderstand a subject's symptoms. As noted above, however, in certainother embodiments, the display unit may not be programmed to alert asubject, but instead may simply be left available for a subject to inputdata regarding his or her symptoms or to select movement disorderassessment tasks to perform from among various options according to thesubject's personal preferences and schedule as well as the subject's ownsubjective view of the severity of his or her symptoms.

By way of a more specific example of the above situation, a physician orother clinician may see a subject for treatment of PD or other movementdisorders and the subject may indicate to the physician that his or hersymptoms associated with PD or other movement disorders vary greatlythroughout the day. To better understand the diurnal fluctuations of thesubject's symptoms and to be better able to tune the movement disordertherapy device, the physician may program a display unit tointermittently alarm over a certain duration of time and to instruct thesubject to, for example, wear the sensor on the subject's right handwhile performing hand grasping exercises, finger tapping exercises andto simply wear the sensor for a period of time while resting to examinethe severity of a subject's rest tremor.

In the embodiment illustrated in FIG. 1, the subject 1 performs amovement disorder test according to instructions. Optionally, theseinstructions may be provided by an instructional video clip displayed ona the user interface 7 of the tablet computer 6, advantageouslyproviding the subject with a standardized visual aid to mirror while atest is conducted and data is collected. Such a system implemented insoftware and provided through user interface 7 ensures the same clinicalexamination protocol is used subsequent office visits, advantageouslyallowing clinicians to more repeatedly and objectively track symptomsand assuring inter-subject data correspondence. Alternately, the subject1 may simply follow instructions given by a clinician. Preferably,testing includes (or may be limited to) three types of tremor tasks(resting, postural, and kinetic) and three types of bradykinesia tasks(finger tapping, hand grasps, and pronation/supination). Eitheralternatively or in addition, testing may include various gait/balancetasks as well. The sensor unit 2 collects data which is sent to commandmodule 3 for transmission via radio link to a receiver unit 5. Theprocessor of the tablet computer 6 processes the movement data toextract kinematic features which are then fed into a trained algorithmimplemented as a software algorithm in the tablet computer 6. Thetrained algorithm may output a score which may then be displayed on theuser interface 7. The processor of tablet computer 6 then computessuggested therapy device parameter settings based at least in part uponthe current therapy device parameter settings and the collected movementdata and/or the quantified score computed therefrom. An exemplary tuningalgorithm for computing the suggested therapy device parameter settingsis illustrated in FIG. 3. The clinician may input the existing therapydevice parameter settings into the user interface 7, or the tabletcomputer 6 may communicate directly with the programmer unit 8, wired orwirelessly, to ascertain preexisting parameter settings.

Once suggested parameter settings adjustments are computed by the tuningalgorithm, the adjustments or new settings are displayed on the userinterface 7. They may then be manually entered into the programmer unit7 for reprogramming of the therapy device, or the tablet computer 6 maycommunicate directly with the programmer unit 8, wired or wirelessly, toadjust the parameter settings.

The therapy device may be reprogrammed wired or wirelessly, and typicalimplanted therapy devices are enabled with means of wirelesstranscutaneous reprogramming.

The alternate embodiment of the invention depicted in FIG. 2advantageously combines the receiver unit 5, the tablet computer 6, theuser interface 7, and the programming unit 8 into one clinician unit 9having improved user interface 10, which is preferably a touch-screeninterface. The command module 3 transmits movement data acquired by thesensor unit 2, as described above, to the clinician unit 9, where themovement data is analyzed and parameter settings adjustments arecomputed. The parameter settings may then be automatically orsemi-automatically updated, with the clinician unit 9 interfacing withthe therapy device (not shown) directly to reprogram the therapydevice's parameter settings. In the case of a semi-automatic update ofparameter settings, the improved user interface 10 provides a prompt,which may consist of, for example, a button or an audio query. Responseto the prompt (e.g., pressing the button or giving a vocal command)initiates the therapy device reprogramming.

Preferably, the touch screens of tablet computer 6 and clinician unit 9permit the clinician to interact with the user interface 7 or theimproved user interface 10 using a large sterile stylus (not shown).

In alternate embodiments of the invention, quantification of movementdisorder symptoms may be performed using a different form of movementmeasuring apparatus. In one such example, a webcam built into the tabletcomputer 6 or clinician unit 9, or a video camera or set of multiplecameras connected thereto, view the subject 1 performing the motiondisorder test and feed video data into the tablet computer 6 orclinician unit 9 where, for example, machine vision algorithms measurethe motion of the limbs of the subject with respect to time according toany method known in the art. Such a method may consist, for example, indetermining marker points along the limb of the subject in order togauge relative motion, and such a method may be assisted by applyingmore visible markers (not shown) on various points on the limb of asubject 1, such as is common with motion capture technology. In suchcase, the need for sensor unit 2, with its accelerometers andgyroscopes, may be obviated.

In a preferred embodiment, a programming session will be carried outaccording to a protocol comprising the following steps. The clinicianwill assess all motor task baseline scores. The clinician will checkelectrode impedance for wire damage. The clinician will recordmedication dosages, which information preferably includes informationrelevant to the subject's present level of medication, such as time anddosage of last medication administration. The clinician will selectprogramming motor tasks, and in conjunction with the programmer unit 8,9, the subject will repeat the series of motor tasks for eachstimulation setting. The clinician will then enter the DBS settings andcorresponding scores for each chosen motor task, with the ability toswitch between tasks for entering data and selecting which DBSparameters are fixed: frequency, current, pulse width, and contact setup(mono, bi, tripolar). Finally, the clinician will assess all motor taskspost-programming. Preferably, the system will provide the ability toenter DBS settings and scores completely either with a finger or styluson a touch screen, and/or with a mouse and/or with a keypad or keyboardusing the tab key to switch between data input fields. Preferably, thesystem provides three data input modes: (1) enter stimulation and scoreinformation, click update, enter next measurement; (2) enter informationand display updated tuning map; (3) use stylus/finger/mouse to click onthe tuning map for the appropriate measurement, with a new input boxappearing to enter score/side effects/notes.

It is advantageous in some embodiments for the system to permit theclinician performing the programming session to enter a large number ofvariables in order to provide a complete assessment of the DBS tuning.The following is a representative list of information which may beentered in each programming session: (1) general subject information,including patient ID, whether the subject's DBS implant is unilateral orbilateral, implant electrode site location and side; (2) motor tasksperformed during tuning, including (a) tremor: rest, postural, kinetic,(b) bradykinesia: finger tap, hand grasp, pronate/supinate, (c)rigidity: elbow/knee, head/neck, (d) leg agility: heel tapping, (e)rising from chair: with arms crossed, (f) posture, (g) gait: walkingquality, (h) postural stability: pull back; (3) motor scores, in theform of integer scoring from 0 (no severity) to 4 (extremelydebilitating); (4) DBS settings, including (a) contact: cathode/anode,monopolar (case (battery pack)+, 0 to 3 neg)/bipolar, contact 0 is thedeepest, (b) stimulation parameters including amplitude (in volts),frequency (in Hz), current (in amps), pulse width (in microseconds), (c)side effects and/or capsule effects, including (i) motor effects, suchas worsening of symptoms, dyskinesias, facial pulling, (ii) non-motoreffects, such as blurry vision, soft or slurred speech, sweating,headache, tingling (transient/non-transient), fatigue, sense ofeuphoria, (iii) new or atypical side effects and update list of notableeffects

Details of the process of movement disorder symptom score calculationare described in this application's parent application, U.S. patentapplication Ser. No. 12/250,792, which is herein incorporated byreference.

FIG. 3 shows an example tuning algorithm used for computing suggestedparameter settings adjustments. This basic algorithm utilizes symptomseverity data, detected stimulation induced dyskinesias (SID), andclinical inputs such as clinician defined improvement percentage (CDI %)to compute suggested stimulation parameter settings. Based on thetypical clinical description, several constraints reduce the number ofdegrees of freedom in the tuning algorithm. During DBS programming, theclinician may utilize any subset of the motor task mentioned previouslyto evaluate motor performance. The average tremor score (ATS) iscomputed for the set of tremor tasks and the average bradykinesia score(ABS) is computed for the set of bradykinesia tasks utilized by theclinician for a given iteration. This reduces the number of symptomseverity outputs from a maximum of three to one for each symptom.Dyskinesia is either “on” or “off.”

Recording symptom severity before the therapeutic device is turned onobtains baseline. In the case of DBS adjustment, before utilizing thetuning algorithm, the best monopolar electrode contact is determined byfinding the contact that provides the largest therapeutic width, i.e.,the largest change in supplied voltage from when a clinical benefit isnoticed to when side effects occur. This is accomplished by fixingstimulation pulse width to 60 μs, frequency to 130 Hz, selecting onecontact, and then stepping the voltage amplitude in small increments ofapproximately 0.2 V. The procedure is repeated for each contact. Thecontact that provides the largest therapeutic width is selected. Withthe pulse width (60 μs) and frequency (130 Hz) set to typical values,the clinician then sets the amplitude to the lowest voltage thatprovides a significant decrease in symptoms. If a satisfactory result isnot achieved, pulse width or frequency may also be increased. This canbe a time consuming iterative process that must be completed severaltimes over the first few months as microlesioning heals and requires acompensatory increase in stimulation amplitude to maintain clinicalbenefit. In various embodiments, the invention includes a sensitivetool, implemented in software and accessed through user interface 7 orimproved user interface 10 to detect the instant of clinical benefit asvoltage amplitude is increased and the instant any stimulation induceddyskinesias are detected. Use of the invention as a sensitive measure ofclinical benefit onset and side effect occurrence advantageously ensuresthe contact with the greatest therapeutic width is selected.

Once the contact width is selected, the initial parameter settingsadjustment iteration may be completed with literature-defined settingsof 60 μs and 130 Hz stimulation. Amplitude is set to 0.2 V initially,then modified by the clinician in subsequent iterations. After eachstimulation parameter change, the clinician uses the user interface 7 orthe improved user interface 10 and guides the subject through motortasks. The tuning algorithm output provides a suggested parameterdirection output after each motor task evaluation by utilizing themovement disorder quantification algorithm. The invention therebymaximizes clinical benefit by minimizing tremor and bradykinesia,minimizes adverse effects of stimulation-induced dyskinesias, andminimizes current consumption to maximize battery life. Thus, oneobjective function is to minimize the sum of average tremor score (ATS)and average bradykinesia score (ABS), known as the summed motor score(SMS) 11. This objective is achieved in the tuning algorithm bycontinuing to increase stimulation in the same direction as long as SMSis decreasing. A higher SMS corresponds to worse motor symptoms. Asecond constraint is that stimulation induced dyskinesias (SID) shouldnot occur. If they are detected, the direction of the parameter changeis reversed. Another system constraint is the minimization currentconsumption. This is accomplished by allowing a clinician definedimprovement percentage (CDI %) 12 and considering any changes of lessthan 5% in SMS to be insignificant. When these conditions are met, thecurrent parameter level is maintained 13 due to the SMS goal beingachieved and with consideration given to diminishing clinical returns,in order to maximize battery life. Once optimized amplitude has beenachieved or reaches 3.6 V, the clinician may adjust pulse width orfrequency utilizing the same algorithm. The chances of the feedbacksystem settling into local minimums are reduced by ensuring several ofthe settings are set at clinically accepted levels for the initialiteration and making only moderate adjustments as required.

While manual DBS programming frequently entails stepping through smallincremental changes, this process can be wastefully time-consuming ifthe motor symptom response of the subject indicates larger changes arerequired. The implementation of an artificial neural network 14 tooutput suggested stimulation parameters minimizes programming iterationsto reduce surgical and outpatient tuning session time.

Preferably, the artificial neural network 14 used in the tuningalgorithm used by some embodiments of the present invention is trainedwith recorded clinician-made stimulator parameter changes in response tomotor symptom severity changes during stimulator programming to minimizerequired iterations while still utilizing objective symptom severitymeasures to optimize performance. In this way, the algorithm takesclinician experience into account. Experienced clinicians are generallysuccessful in quickly reducing the number of potentially successfulparameter settings for tuning DBS systems. An expert clinician iscapable of recognizing severe motor symptoms and modifying a parameterby a larger magnitude, then when the symptom is less and onlyfine-tuning is required. The present invention is therefore capable ofquantitatively detecting motor symptom severity and suggesting aparameter change that approximates or mirrors the parameter change thatwould be made by an expert clinician.

Artificial neural network 14 may be implemented, for example, with theMATLAB Neural Network Toolbox offline using resilient backpropagationbatch training. Inputs to the neural network may include current andprevious stimulation settings 15 and motor responses.

FIG. 4 illustrates a two-layer network structure consisting of onehidden layer 17 with four neurons using “tansig” transfer functions andone output layer 18. As neural networks may fall into local minimumswhen being trained, each network is preferably trained three times withrandomized initial weights and biases and the best training results areselected. Additionally, early stopping improves network generalization.Data is separated into training and generalization sets to ensuretrained networks produce accurate results both when the training set isreapplied and also when it is generalized to new data. Preferably,training data is collected from multiple patients. To ensure that thesystem generalizes to new patients, network generalization can be testedby training the system using a jackknife “one left out” method. Usingsuch a method, the neural network is trained using data from, forexample, only nine of ten subjects. Data from the nine subjects in thetraining set is then reapplied to the trained network to ensure goodcorrelations while data from the “left out” subject is used to testgeneralization. The method is repeated, leaving out each subject onetime. For each training and generalization set, both the mean squarederror (MSE) and R-squared values between the clinician-made stimulatorparameter changes and those output by the system for each stimulationparameter are calculated. The MSE and R-squared for all training andgeneralization sets are averaged. Preferably, the system achievesnormalized MSE values of less than 10% and R-squared values of greaterthan 0.8 to show substantial agreement between system-suggestedsimulation parameter changes and clinician-made stimulation parameterchanges.

Preferably, separate data sets and acquired, and separate neuralnetworks are trained, for the surgical and outpatient scenarios.Preferably, the data used to train the algorithm averages the experienceof multiple expert clinician programmers.

Preferably, the tuning algorithm comprises a neural network asillustrated in FIG. 3, but it might instead or in addition comprise oneor more of adaptive continuous learning algorithms, linear quadraticGaussian control, Kalman filtering, and model predictive control.

When the tablet computer 6 is connected to the Internet or similarcommunications network, wired or wirelessly, it may therefore transmitsubject data to remote systems, allowing general practitioners toconduct DBS programming remotely, minimizing travel for a subject 1 wholives far from a DBS implantation center or suitable programming clinic,so long as the subject 1 is equipped with the sensor unit 2/commandmodule 3 and means of programming and/or making parameter settingsadjustments to his or her therapy device (including DBS implant).

FIG. 5 depicts a series specific display pages corresponding toreporting score provided in various embodiments of the presentinvention. These examples of methods of reporting scores with visualdisplays associated with each display stage of the test process aremerely exemplary. One example of a displaying a score is the expandablemenu view 19, where the user (i.e., clinician, physician, or patientperforming self-testing away from the clinician) is presented with alist of the different types of movement disorders or movement disordersymptoms which may or may not have been measured in a given test. In theportrayed example of this expandable menu view 19, the movement disordersymptoms that may be selected include tremor, bradykinesia, rigidity andgait. The user is then given the option of expanding the results foreach of those movement disorders or movement disorder symptoms through aseries of levels (i.e., hand then to left or right), in order to viewthe score that was determined for each particular disorder or symptom inthe indicated portion of the subject's body. By way of clarification andexample, the subject shown in menu view 19 received a score of 1 duringrest for the symptom of tremor in the left hand, and a 2 for thepronation/suppination task for bradykinesia in the left hand.

Another display method, which may be independent or used in conjunctionwith the expandable menu view is the tuning map 20. A tuning map 20 isgenerated for each task that the subject is directed to perform anddepicts the severity of the symptoms measured in each sensor that isused for the given task. Each task that is performed is represented on adifferent tab (i.e., tab A, tab B, tab C). The amplitude 21 at which thetest was performed is measured in volts and indicated on one verticalaxis of the tuning map 20. The calculated or estimated score 22 isdepicted on a vertical axis of the tuning map 20 as well. Eachindividual box that is shown represents a test performed 24. Preferably,the tuning map 20 is shown on a color display (not shown) and theseverity of the symptom is indicated not by color. In this drawing, thecolors are represented by different types of shading or cross-hatching.Each column in the tuning map 20 represents a different contact on theDBS probe. Therefore, each individual test box 24 depicts the results ofperforming a task while administering DBS at a prescribed voltageamplitude 21 and provides both a severity of the symptom which wasdetected or measured by virtue of the color (represented by thecross-hatching) which also correlates to a given motor score.Additionally, each individual test box 24 may be selected, for exampleby pressing it on a touch-screen device, as representing by the testboxes 24 which are outlined in black. When a test box 24 is selected,the user is able to see a detailed view (not shown) of the statisticsand parameters of the test corresponding to that box.

A variable window 25 may display on the unit as well which allows theuser to input various conditions that have an effect on the test andtest results. These variables are calculated into the test results andhelp to give a more accurate calculated symptom score.

FIG. 6 portrays the tuning maps 20 in greater detail. Each taskperformed is represented again by a separate tab with its own tuning map20. The amplitude 21 of the voltage at which the test was performed istracked along one vertical axis of the map 20 for each contact 23 on theDBS lead, while the severity of the symptom detected or measured isdisplayed as a score 22 and correlated to a color of each individualtest box 24. The right side 26 of FIG. 6 portrays a new tab 27 whichrepresents the combination of tabs A and B. This combination tab 27represents the combination of the tuning maps for tasks A and B.

The combination 27 is a result of the user selecting those two tuningmaps to be combined together in some mathematical way (i.e., averaging)in order to show the results of how the scores for each task combine inorder to optimize the DBS level for treating the subject. In otherwords, the goal is to minimize the voltage at which the DBS is to besupplied while simultaneously minimizing the severity of the subject'ssymptoms. Combining the tuning maps for each task allows the user to seea resulting score and select the DBS test parameters which are as closeto optimal as possible. It is also conceivable that the system would bedesigned to be a closed-loop system, (i.e., for an implantedhome-diagnostic and therapeutic device) which would not requireextensive, or any, user input, but would perform the optimizationautomatically.

It will be apparent to those skilled in the art that variousmodifications and variations can be made to the present inventionwithout departing from the spirit and scope of the invention. Thus, itis intended that the present invention cover the modifications andvariations of this invention provided they come within the scope of theappended claims and their equivalents.

We claim:
 1. A system for adjusting the parameters of a deep brainstimulation device implanted in a subject for treating a subject'smovement disorder by a clinician, the system comprising: a sensor unitcomprising at least one sensor for quantifying at least one symptom of asubject's movement disorder having an analog or digital signal relatedto the movement of the subject with a movement disorder, the subjecthaving a deep brain stimulation implant with adjustable parameters; acommand module adapted for receiving and transmitting the analog ordigital signal acquired by the sensor unit or a second digital signalcorresponding to the at least one quantified motor symptom, the commandmodule comprising a memory; a clinician unit comprising a processor anda user interface, the clinician unit adapted for receiving and forprocessing the analog or digital signal acquired by the sensor unit orthe second digital signal, for receiving an input related to thesubject's deep brain stimulation implant's parameter settings in placeduring measurement of the analog or digital signal with the sensor unit,and adapted to produce an output comprising computed adjustments for oneor more of the adjustable parameters of the deep brain stimulationimplant, the output being based at least in part on the signal acquiredby the sensor unit or the second digital signal and at least in part onthe input related to the subject's deep brain stimulation implant'sparameter settings; and a display for receiving the output, wherein thesensor unit and command module are integrated into a single enclosurehaving a volume of no more than or about 82 cubic centimeters and a massof no more than or about 97 grams.
 2. The system of claim 1, wherein thesensor unit comprises at least two sensors for quantifying at least onesymptom of a subject's movement disorder including at least oneaccelerometer and at least one gyroscope.
 3. The system of claim 1,wherein the output of the clinician unit comprises at least one tuningmap depicting optimal DBS lead setting parameters based on thequantified severity of the at least one motor symptom with the tuningmap output being in color, shading or cross-hatching on the display. 4.The system of claim 1, wherein the clinician unit is a smartphone ortablet computer.
 5. The system of claim 1, wherein the at least oneadjustable parameter is one or more parameters selected from the groupconsisting of stimulation frequency, amplitude, current, pulse width,and contact configuration.
 6. The system of claim 1, further comprisingan interface adapted for providing the deep brain stimulation implantwith the output.
 7. The system of claim 6, wherein the output isprovided to the subject's deep brain stimulation device via theinterface automatically or upon manual or vocal confirmation of thepresented estimated or calculated level of adjustment, the confirmation,if used, being made by a medical professional or the subject.
 8. Asystem for adjusting the parameters of a deep brain stimulation deviceimplanted in a subject for treating a subject's movement disorder by aclinician, the system comprising: a sensor unit comprising at least onesensor for quantifying at least one symptom of a subject's movementdisorder having an analog or digital signal related to the movement ofthe subject with a movement disorder, the subject having a deep brainstimulation implant having adjustable parameters; a command moduleadapted for receiving and transmitting the analog or digital signalacquired by the sensor unit or a second digital signal corresponding tothe at least one quantified motor symptom, the command module comprisinga memory; a clinician unit comprising a processor and a user interface,the clinician unit adapted for receiving and for processing the analogor digital signal acquired by the sensor unit or the second digitalsignal, for receiving an input related to the subject's deep brainstimulation implant's parameter settings in effect during measurement ofthe analog or digital signal with the sensor unit, and to produce anoutput comprising computed adjustments for one or more of the adjustableparameters of the deep brain stimulation implant, the output being basedat least in part on the analog or digital signal acquired by the sensorunit or the second digital signal and at least in part on the inputrelated to the subject's deep brain stimulation implant's parametersettings; a display for receiving the output; and an interface adaptedfor providing the deep brain stimulation implant with the output,wherein the sensor unit and command module are integrated into the samea single enclosure having a volume of no more than or about 82 cubiccentimeters and a mass of no more than or about 97 grams.
 9. The systemof claim 8, wherein the sensor unit comprises at least two sensors forquantifying at least one symptom of a subject's movement disorderincluding at least one accelerometer and at least one gyroscope.
 10. Thesystem of claim 8, wherein the output of the clinician unit comprises atleast one tuning map depicting optimal DBS lead setting parameters basedon the quantified severity of the at least one motor symptom with thetuning map output being in color, shading or cross-hatching on thedisplay.
 11. The system of claim 8, wherein the clinician unit is asmartphone or tablet computer.
 12. The system of claim 8, wherein theoutput is provided to the subject's deep brain stimulation device viathe interface automatically or upon manual or vocal confirmation of thepresented estimated or calculated level of adjustment, the confirmation,if used, being made by a medical professional or the subject.
 13. Thesystem of claim 8, further comprising a closed loop control systemadapted for adjusting the at least one adjustable parameterautomatically based at least in part on the computed adjustments for theat least one adjustable parameter.
 14. The system of claim 8, whereinthe display is further adapted to provide an audible, visual orcombination thereof alert to the subject of the need to perform at leastone movement disorder evaluation tasks and to provide instructions tothe subject on how to properly complete the at least one movementdisorder evaluation task.
 15. A system for adjusting the parameters of adrug delivery pump used with a subject for treating a subject's movementdisorder by a clinician, the system comprising: a sensor unit comprisingat least one sensor unit for quantifying at least one symptom of asubject's movement disorder, the sensor unit having an analog or digitalsignal related to the movement of the subject with a movement disorder,the subject having a drug delivery pump having adjustable parameters; acommand module being adapted for receiving and transmitting the analogor digital signal acquired by the sensor unit or a second digital signalcorresponding to the at least one quantified motor symptom; a clinicianunit comprising a processor and a user interface, the clinician unitadapted for receiving and processing the analog or digital signalacquired by the sensor unit or the second digital signal, for receivingan input related to the subject's drug delivery pump's historicalparameter settings in effect prior to and during measurement of theanalog or digital signal with the sensor unit, and for producing anoutput comprising computed adjustments for one or more of the adjustableparameters of the drug delivery pump, the output being based at least inpart on the analog or digital signal acquired by the sensor unit or thesecond digital signal and at least in part on the input related to thesubject's drug delivery pump historical parameter settings; and adisplay for receiving the output wherein the sensor unit and commandmodule are integrated into a single enclosure having a volume of no morethan or about 82 cubic centimeters and a mass of no more than or about97 grams.
 16. The system of claim 15, wherein the output of theclinician unit comprises optimal drug delivery pump parameter settingsbased on the quantified severity of the at least one motor symptoms. 17.The system of claim 15, wherein the output is provided to the subject'sdrug delivery implant via an interface automatically or upon manual orvocal confirmation of the presented estimated or calculated level ofadjustment, the confirmation being made, if used, by a medicalprofessional or the subject.
 18. The system of claim 15, wherein thesensor unit comprises at least two sensors including a gyroscope and anaccelerometer.
 19. The system of claim 15, further comprising a closedloop control system adapted for adjusting the at least one adjustableparameter of the drug delivery pump automatically based at least in parton the computed adjustments for the at least one adjustable parameter.20. The system of claim 19, wherein the display is further adapted toprovide an audible, visual or combination thereof alert to the subjectof the need to perform at least one movement disorder evaluation tasksand to provide instructions to the subject on how to properly completethe at least one movement disorder evaluation task.